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## llm-wiki.md

      
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                karpathy
                / llm-wiki.md
            
            
              Created
              April 4, 2026 16:25
            
              
                llm-wiki
              
          
    LLM Wiki

A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

  
## install-battlenet-on-cachyos-linux-steam-proton.md

      
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                kriegalex
                / install-battlenet-on-cachyos-linux-steam-proton.md
            
            
              Last active
              September 16, 2026 03:16
            
              
                Install Battle.net on CachyOS Linux Using Steam & Proton
              
          
    Install Battle.net on CachyOS Linux Using Steam & Proton


Tested on: CachyOS (Arch-based) · KDE Plasma 6.5 / 6.6 · Wayland · Steam (native pacman package)
Last updated: March 2026
Games confirmed working: World of Warcraft, Diablo IV, Diablo II: Resurrected, StarCraft Remastered, Hearthstone, Overwatch 2, Call of Duty

Why This Method?


## officeActivator.bat
@echo off
title Activate Microsoft Office 2019 !
cls
echo ============================================================================
echo #Project: Activating Microsoft software products
echo ============================================================================
echo.
echo #Supported products:
echo - Microsoft Office Standard 2019
echo - Microsoft Office Professional Plus 2019

## Traditional.txt
一丁七三下丈上丑丐不丙世丕且丘丞丟並丫中串丸凡丹主乃久么之尹乍乏乎乒乓乖乘乙九也乞乩乳乾亂了予事二于云井互五亙些亞亟亡交亦亥亨享京亭亮人仁什仃仆仇仍今介仄以付仔仕他仗代令仙仞仿伉伙伊伕伍伐休伏仲件任仰仳份企位住佇佗佞伴佛何估佐佑伽伺伸佃佔似但佣作你伯低伶余佝佯依侍佳使佬供例來侃佰併侈佩佻侖佾侏信侵侯便俠俑俏保促侶俘俟俊俗侮俐俄係俚俎俞倌倍倣俯倦倥俸倩倖倆值借倚倒們俺倀倔倨俱倡個候倘俳修倭倪俾倫倉偺偽停假偃偌做偉健偶偎偕偵側偷偏倏傢傍傅備傑傀傖傘傭債傲傳僅傾催傷傻傯僧僮僥僖僭僚僕像僑僱億儀僻僵價儂儈儉儒儘儔儐優償儡儲儷儼兀元允充兄光兇兆先兌克兕免兔兒兗兜兢入內全兩八六兮公共兵具其典兼冀冉冊再冒冑冕最冗冠冤冥冢冬冰冶冷冽凍凌准凋凜凝几凰凱凳凶凹出凸函刀刁刃分切刈刊列刑划刎別判利刪刨刻券刷刺到刮制剁剎剃削前剌剋則剖剜剔剛剝剪副割剴創剩剿剷剽劃劇劈劉劍劑力加功劣劫助努劬劾勇勉勃勁勒務勘動勞勝勛募勦勤勢勵勸勻勾勿包匆匈匍匐匏匕化北匙匝匡匠匣匪匯匱匹匿區匾十千午升卅仟半卉卒協卓卑南博卜卞卡占卦卯卮印危即卵卷卸卹卻卿厄厚原厝厥厭厲去參又叉友及反取叔受叛叟曼叢口可古右召叮叩叨叼司叵叫另只史叱台句叭吉吏同吊吐吁吋各向名合吃后吆吒吝吭吞吾否呎吧呆呃吳呈呂君吩告吹吻吸吮吵吶吠吼呀吱含吟味呵咖呸咕咀呻呷咄咒咆呼咐呱呶和咚呢周咋命咎咬哀咨哎哉咸咦咳哇哂咽咪品哄哈咯咫咱咻哨唐唁唷哼哥哲唆哺唔哩哭員唉哮哪哦唧商啪啦啄啞啡啃啊唱啖問啕唯啤唸售啜唬啣唳啻喀喧啼喊喝喘喂喜喪喔喇喋喃喳單喟唾喲喚喻喬喱啾喉嗟嗨嗓嗦嗎嗜嗇嗑嗣嗤嗯嗚嗡嗅嗆嗥嗾嘀嘛嘗嗽嘔嘆嘉嘍嘎嗷嘖嘟嘈嘮嘻嘹嘲嘿嘩噓噎噗噴嘶嘯嘰噙噫噹噩噤噸嘴噪器噥噱噯噬噢嚎嚀嚐嚅嚇嚏嚕嚮嚥嚨嚷嚶嚴嚼囁囀囂囈囊囉囌囑四囚因回囪困囤固圃圈國圍園圓團圖土圳地在圭圬圯坊坑址坍均坎圾坐坏垃坷坪坩坡坦坤坼垂型垠垣垢城垮埂埔埋埃域堅堊堆埠埤基堂堵執培堯堪場堤堰報堡塞塑塘塗塚塔填塌塭塊塢塵塾境墓墊塹墅墀墟增墳墜墮壁墾壇壅壕壓壑壙壘壞壟壢壤壩士壬壯壹壺壽夏夔夕外夙多夜夠夥夢夤大天夫太夭央失夷夸夾奉奇奈奄奔奕契奏奎奐套奘奚奢奠奧奪奩奮女奴奶妄奸妃好她如妁妝妒妨妞妣妙妖妍妤妓妊妥妾妻委妹妮姑姆姐姍始姓姊妯妳姒姜姘姿姣姨娃姥姪姚姦威姻娑娘娜娟娛娓姬娠娣娩娥娌娶婁婉婦婪婀娼婢婚婆婊婷媚婿媒媛嫁嫉嫌媾媽媼媳嫂媲嫡嫦嫩嫗嫖嫘嫣嬉嫻嬋嫵嬌嬝嬴嬰嬪嬤嬸孀子孑孓孔孕字存孝孜孚孟孤季孩孫孰孳孱孵學孺孽孿它宇守宅安完宋宏宗定官宜宙宛宣宦室客宥宰

## microgpt.py
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

## Hyper-V GPU-PV with Linux guest.md

      
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                krzys-h
                / Hyper-V GPU-PV with Linux guest.md
            
            
              Last active
              September 16, 2026 02:52
            
              
                Ubuntu 21.04 VM with GPU acceleration under Hyper-V...?
              
          
    Ubuntu 21.04 VM with GPU acceleration under Hyper-V...?

Modern versions of Windows support GPU paravirtualization in Hyper-V with normal consumer graphics cards. This is used e.g. for graphics acceleration in Windows Sandbox, as well as WSLg. In some cases, it may be useful to create a normal VM with GPU acceleration using this feature, but this is not officially supported. People already figured out how to do it with Windows guests though, so why not do the same with Linux? It should be easy given that WSLg is open source and reasonably well documented, right?
Well... not quite. I managed to get it to run... but not well.
How to do it?


Verify driver support


## multiple_ssh_setting.md

      
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                jexchan
                / multiple_ssh_setting.md
            
            
              Created
              April 10, 2012 15:00
            
              
                Multiple SSH keys for different github accounts
              
          
    Multiple SSH Keys settings for different github account

create different public key

create different ssh key according the article Mac Set-Up Git
$ ssh-keygen -t rsa -C "your_email@youremail.com"


## conventional-commits-cheatsheet.md

      
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                qoomon
                / conventional-commits-cheatsheet.md
            
            
              Last active
              September 16, 2026 02:50
            
              
                Conventional Commits Cheatsheet
              
          
    Conventional Commit Messages 


See how a minor change to your commit message style can make a difference.
git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"
	@echo off
	title Activate Microsoft Office 2019 !
	cls
	echo ============================================================================
	echo #Project: Activating Microsoft software products
	echo ============================================================================
	echo.
	echo #Supported products:
	echo - Microsoft Office Standard 2019
	echo - Microsoft Office Professional Plus 2019
	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp